Daniel T. Mainz
Impact in
- Computational Theory and Mathematics top 0.02%
- Computational Drug Discovery Methods
- Molecular Biology top 0.5%
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- Cancer therapeutics and mechanisms
- Chemical Synthesis and Analysis
Papers in
-
- Computational Drug Discovery Methods 3
- Co-authors
- Richard A. FriesnerMatthew P. RepaskyThomas A. HalgrenRobert B. MurphyJay L. BanksLeah L. FryeJeremy R. GreenwoodPaul C. Sanschagrin
- Journals
- The Journal of Chemical Physics (3 papers)Journal of Computational Chemistry (2 papers)Journal of Medicinal Chemistry (2 papers)Biochemistry (1 paper)Computational and Theoretical Polymer Science (1 paper)
- Partner nations
- United States
In The Last Decade
Daniel T. Mainz
11 papers receiving 14.5k citations
Hit Papers
Peers
Comparison fields: 5 of 156
- Computational Theory and Mathematics 4.8k
- Molecular Biology 9.0k
- Toxicology 417
- Organic Chemistry 3.4k
- Pharmacology 1.7k
Countries citing papers authored by Daniel T. Mainz
This map shows the geographic impact of Daniel T. Mainz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel T. Mainz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T. Mainz more than expected).
Fields of papers citing papers by Daniel T. Mainz
This network shows the impact of papers produced by Daniel T. Mainz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel T. Mainz. The network helps show where Daniel T. Mainz may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel T. Mainz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 17 | |
| 2 | Extra Precision Glide: Docking and Scoring Incorporating a Model of Hydrophobic Enclosure for Protein−Ligand Complexes Hit paper breakdown → | 2006 | 5413 |
| 3 | Integrated Modeling Program, Applied Chemical Theory (IMPACT) Hit paper breakdown → | 2005 | 1195 |
| 4 | Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy Hit paper breakdown → | 2004 | 7559 |
| 5 | 2001 | 34 | |
| 6 | 2001 | 139 | |
| 7 | 2000 | 12 | |
| 8 | 1999 | 220 | |
| 9 | 1998 | 2 | |
| 10 | 1997 | 5 | |
| 11 | 1994 | 121 |
About Daniel T. Mainz
Daniel T. Mainz is a scholar working on Computational Theory and Mathematics, Spectroscopy, Polymers and Plastics, Atomic and Molecular Physics, and Optics and Radiation, having authored 11 papers that have together received 14.7k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (4 papers), Advanced Chemical Physics Studies (4 papers), Spectroscopy and Quantum Chemical Studies (3 papers), Computational Drug Discovery Methods (3 papers), Chemical Synthesis and Analysis (2 papers), Advanced Polymer Synthesis and Characterization (2 papers), Dendrimers and Hyperbranched Polymers (2 papers) and Glycosylation and Glycoproteins Research (1 paper). The work is most often cited by research in Computational Theory and Mathematics (4.8k citations), Molecular Biology (9.0k citations), Toxicology (417 citations), Organic Chemistry (3.4k citations) and Pharmacology (1.7k citations). Daniel T. Mainz has collaborated with scholars based in United States. Frequent co-authors include Richard A. Friesner, Matthew P. Repasky, Thomas A. Halgren, Robert B. Murphy, Jay L. Banks, Leah L. Frye, Jeremy R. Greenwood, Paul C. Sanschagrin, Jasna Klicić and Jason K. Perry. Their work appears in journals such as The Journal of Chemical Physics, Journal of Computational Chemistry, Journal of Medicinal Chemistry, Biochemistry and Computational and Theoretical Polymer Science.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.